On computational models of animal movement behaviour

Finding structures and patterns in animal movement data is essential towards understanding a variety of behavioural phenomena, as well as shedding light into the relationships between animals among conspecifics and across different taxa with respect to their environments. The recent advances in the field of computational intelligence coupled with the proliferation of low-cost telemetry devices have made the gathering and analyses of behavioural data of animals in their natural habitat and in a wide range of context possible with aid of devices such as Global Positioning System (GPS). The sensory input that animals receive from their environment, and the corresponding motor output, as well as the neural basis of this relationship most especially as it affects movement, encode a lot of information regarding the welfare and survival of these animals and other organisms in nature's ecosystem. This has huge implications in the area of biodiversity monitoring, global health and understanding disease progression. Encoding, decoding and quantifying these functional relationships however can be challenging, boring and labour intensive. Artificial intelligence holds promise in solving some of these problems and even stand to benefit as understanding natural intelligence for instance can aid in the advancement of artificial intelligence. In this thesis, I investigate and propose several computational methods leveraging information theoretic metrics and also modern machine learning methods including supervised, unsupervised and a novel combination of both towards understanding, predicting, forecasting and quantifying a variety of animal movement phenomena at different time scales across different taxa and species. Most importantly the models proposed in this thesis tackle important problems bordering on human and animal welfare as well as their intersection. Crucially, I investigate several information theoretic metrics towards mining animal movement data, after which I propose machine learning and statistical techniques for automatically quantifying abnormal movement behaviour in sheep with Batten disease using unsupervised methods. In addition, I propose a predictive model capable of forecasting migration patterns in Turkey vulture as well as their stop-over decisions using bidirectional recurrent neural networks. And finally, I propose a model of sheep movement behaviour in a flock leveraging insights in cognitive neuroscience with modern deep learning models. Overall, the models of animal movement behaviour developed in this thesis are useful to a wide range of scientists in the field of neuroscience, ethology, veterinary science, conservation and public health. Although these models have been designed for understanding and predicting animal movement behaviour, in a lot of cases they scale easily into other domains such as human behaviour modelling with little modifications. I highlight the importance of continuous research in developing computational models of animal movement behaviour towards improving our understanding of nature in relation to the interaction between animals and their environments

Characterization, Proximate Composition and Evaluation of Antimicrobial Activity of Seed Oil of Bauhinia tomentosa

Background: This study was carried out to investigate proximate composition, phytochemical profile and antimicrobial activity of the spectroscopically characterized seed oil of Bauhinia tomentosa . Materials and method: The characterization was carried out using FT-IR, mass spectra, 1H- and 13C-NMR. Results: The results from the proximate analysis showed the presence of crude protein 30.36±0.98%, crude fibre 26.00±0.69%, carbohydrate 25.32±0.57%, moisture content 12.04±0.39%, ash content 4.00±0.15% and fat content 2.28±0.09%. The phytochemical screening revealed the presence of alkaloids, flavonoids, saponins, terpenes, cardiac glycosides, sterols, anthraquinones and tannins in varying degrees. The mineral determination showed that the seed oil contained iron (3.10±0.01 mg kgG1),manganese (0.38±0.01 mg kgG1), while cadmium (0.0 mg kgG1), lead (0.0 mg kgG1) and nickel (0.0 mg kgG1) were not detected. The extracted seed oil was investigated for antimicrobial efficiency against four bacterial isolates and two fungal, wherein gentamicin and clotrimazole were the clinical standard antibiotic and antifungal agents, respectively. Conclusion: The antimicrobial activity result revealed the sample to be bioactive and of great pharmaceutical potential with MIC value of 6.25 and <3.625 mg mLG1 against Escherichia coli and Candida albican, respectively. Due to high nutritional values and broad antimicrobial properties, the seed oil of Bauhinia tomentosa has nutraceutical potentials, which might pave way for its use as an alternative nutrient source for mankind or for industrial purposes

Experimental investigation of heat transfer performance of novel bio-extract doped mono and hybrid nanofluids in a radiator

Please read abstract in the article.https://http//www.elsevier.com/locate/csitehb2022Mechanical and Aeronautical Engineerin

Norms of Ambivalence in Setting, Plot and Point-of-View in the Anti-Realist World of Salman Rushdie and Ben Okri

“Inbetweeness”, a cardinal source of strength and weakness of the colonized writer, is an indispensable element in postcoloniality, emphasizing its hybrid nature. Leaning on contextual equivocation, to the “periphery”, seems to be an antidote to the certainty that the “centre” ennobles with evangelistic vigour. The transcendence-driven postcolony exploits the lithe structure of the novel genre to essay dismantling literary frontiers to reflect ideological vagueness and obscurity, which are antipodal to Western bourgeois lucidity. This article, against this background, explicates how Salman Rushdie and Ben Okri, build setting, plot and point-of-view to stem the tide of cultural subordination through imaginative contrarieties.

Biosynthesis and characterization of CuO nanoparticles from plant of Adenathera pavonina linn bark and leaves.

Copper, a naturally occurring element, has medicinal potential and has recently gained in the textile industry. This paper seeks to chart the way forward on the commercial production of copper nanoparticles (Cu-NPs) for textile industry. The leaves and bark of Adenathera pavonina linn were used to synthesize copper nanoparticles (Cu-NPs) which are utilized in a range of applications as heterogeneous catalysts in textile industry. Copper nanoparticles were created using a chemical and natural method (Leaf extraction). In the absence of any reducing or stabilizing agents, the assynthesized samples were submitted to a range of analytical techniques in order to learn more about the physical properties of the materials. The radius of the Cu-NP from leave extract ranged from 56 nm – 89 µm with copper, carbon, and oxygen having a composition of 73.31%, 6.40% and 20.29% respectively. Likewise, the radius of CuNP from bark extract ranged from 56 nm – 293 µm with copper, oxygen, carbon, silicon, manganese, and aluminum having a composition of 65%, 24%, 1.22%, 4.20%, 3.10%, and 2.12% respectively. The impurities are largely from soil which the plant takes its nutrient. Carbon was found in both extract as it is expected in organic compounds in plants. The crystalline characterization shows that their exist a significant composition of Cu (I) species in both Cu-NP from the extracts that makes it highly relevant to the catalytic procedure in the textile industries. Each feature of the planes shows the copper atom represented as Cu-1 and Cu-2. Since Adenathera pavonina linn is in abundant in the tropics, its sustainability and low-cost production and processing are highly desired for textile industries

Phytochemical constituents and proximate analysis of dry pineapple peels

The pineapple and its skin contain a lot of vitamin C, which helps to prevent and fight illnesses. Dry pineapple peel phytochemicals and proximate analysis were investigated in this study. Oil derived from ripe pineapple peels was tested for phytochemical constituents and proximate analysis of dry peel pineapple using a conventional method.Moisture content was 5.10±0.07%, the ash content was 3.78±0.05%, the fat content was 5.57±0.08%, the protein content was 5.78±0.10%, the crude fiber content was 4.10±0.06%, and the carbohydrate content was 75.68±0.86%. Alkaloid phenol, tannin, flavonoid, and saponin were identified as phytochemical components from the result of phytochemical screening.The presence of secondary metabolites in pineapple peel oil is a positive indicator that if thoroughly investigated, bioactive chemicals with significant biological activity may be extracted. As a result, it's plausible to believe that nutraceutical advantages can be derived from this waste (pineapple peel), potentially boosting humanity's prosperity, health and well-being

Effects of Dialium guineense Based Zinc Nanoparticle Material on the Inhibition of Microbes Inducing Microbiologically Influenced Corrosion

This paper investigates the effects of Dialium guineense based zinc nanoparticle material on the inhibition of microbes inducing microbiologically influenced corrosion (MIC) in metals. Extract of leaf from the natural plant were used as precursor for zinc nanoparticle material, which was characterized by scanning electron microscopy and energy dispersive spectroscopy (SEM + EDS) instrument. Sensitivity of the developed zinc bio-nanoparticle material from this on different strains of microbes that are known to induce microbiologically influenced corrosion, in metallic materials, was then studied and compared with that obtained from a commercial antibiotic employed as control. Results showed that the biomaterial capped nanoparticle exhibited inhibited growth of the studied different MIC inducing microbes. Zones of inhibition, the sensitivity measure of the biosynthesized material against the microbial strains either surpassed or compared well with the zones of inhibition from the commercial antibiotic (control). These results engender implication on the prospects of the zinc bio-nanoparticle usages in corrosion inhibition and protection system for metals in microbial corrosion influencing environment

Investigating inhibition of microbes inducing microbiologically-influenced-corrosion by Tectona grandis based Fe-nanoparticle material

In this paper, inhibition of microbes inducing microbiologically-influenced-corrosion (MIC) of metals by Tectona grandis based Fe (iron) Nanoparticle material was investigated. For this, extract was obtained from the leaf of Tectona grandis and this was employed as precursor for synthesizing the Fe-nanoparticle material. From this, the synthesized plant extract based nanoparticle material was characterized using scanning electron microscopy and energy dispersive spectroscopy (SEM+EDS) instrument. The developed Fe bio-nanoparticle material was then employed for sensitivity and/or resistance study application against different strains of microbes that are known to induce microbiologically-influenced-corrosion, in metallic materials, and for this, microbial growth inhibition effect was compared with that from a commercial antibiotic employed as control. Results showed that the Tectona grandis based Fe-nanoparticle exhibited good inhibition effects on the growth of many of the MIC inducing microbes investigated. Sensitivity measures of zone of inhibition against the growth of MIC inducing microbial strains either outperformed or compares well with that obtained from the commercial antibiotic control, in the study. These results indicate positive prospect on the suitability of Fe bio-nanoparticle for corrosion inhibition applications for the protection of metals against microbiological corrosion influencing environment

Incidence and pattern of injuries among adolescent basketball players in Nigeria

<p>Abstract</p> <p>Background</p> <p>Basketball is the second most popular sport in Nigeria after football and is commonly played by adolescents. Prospective studies on adolescent basketball players in Nigeria are lacking. Such studies will help to develop injury counter-measures. Hence, this study aimed at determining the incidence and pattern of injuries among adolescent basketball players in Nigeria.</p> <p>Methods</p> <p>A prospective observational study involving 141 adolescent basketball players (75 boys and 66 girls; with age range 15 – 18 years) who participated in the 2010 National Finals of the Nigeria Nestlé Milo Basketball Competition. Basketball-related injury data were collected by an assessor during the competition using a standardized basketball injury report form. Data were analyzed using descriptive and inferential statistics.</p> <p>Results</p> <p>A total of 32 injuries were recorded with an incidence of 22.7 injuries per 100 participants same for boys and girls. This is equivalent to 1.1 injury per match for boys and 0.9 injuries per match for girls. Jumping/landing was the most common cause of injury (28.1%, N = 9). Most of the injuries were at the lower extremities (75%, N = 24); with majority at the knee joint (40.6%, N = 13). Ligament sprain was the most common types of injury. The pattern of injuries among boys did not significantly differ from that of girls (P > 0.05). Most injuries (N = 13, 41%) occurred in the offensive half of the court and cryotherapy was the most frequently used treatment modality.</p> <p>Conclusion</p> <p>The overall incidence of match injury among adolescent amateur basketball players during a national competition in Nigeria was 22.7 injuries per 100 participants; equivalence of 1.0 injury per match. The pattern of injuries was similar in both genders and consistent with what has been previously reported in literature for adolescent basketball players. Exercise-based injury prevention programmes aimed at improving core strength and neuromuscular control at the lower limbs may help reduce the incidence of injuries.</p